Samsung Technology & Advanced Research Labs, more commonly known as STAR Labs, is all geared up to showcase an artificial intelligence product at CES 2020. STAR Labs is an independent entity of Samsung Electronics and is headed by President & CEO Pranav Mistry who is popularly known for his work on SixthSense. At the time being, the company hasn't revealed much about what Neon is. But their tagline of "Have you ever met an'ARTIFICIAL?", that is sprayed over all social media channels, does suggest that it has to do something regarding artificial intelligence. What SiFi movies have just started exploring, the Indian born scientist @pranavmistry is bringing soon to your home.

Recommendation system models have become one of the most important aspects in customer retention.

What we discover and see online, and consequently our opinions and decisions, are becoming increasingly affected by automated machine learned predictions. Similarly, the predictive accuracy of learning machines heavily depends on the feedback data that we provide them. This mutual influence can lead to closed-loop interactions that may cause unknown biases which can be exacerbated after several iterations of machine learning predictions and user feedback. Machine-caused biases risk leading to undesirable social effects ranging from polarization to unfairness and filter bubbles. In this paper, we study the bias inherent in widely used recommendation strategies such as matrix factorization. Then we model the exposure that is borne from the interaction between the user and the recommender system and propose new debiasing strategies for these systems. Finally, we try to mitigate the recommendation system bias by engineering solutions for several state of the art recommender system models. Our results show that recommender systems are biased and depend on the prior exposure of the user. We also show that the studied bias iteratively decreases diversity in the output recommendations. Our debiasing method demonstrates the need for alternative recommendation strategies that take into account the exposure process in order to reduce bias. Our research findings show the importance of understanding the nature of and dealing with bias in machine learning models such as recommender systems that interact directly with humans, and are thus causing an increasing influence on human discovery and decision making

Hollywood actress Sharon Stone is back on Bumble's dating platform after the matchmaking app reinstated the "Basic Instinct" star's access that was suspended for hours after several users complained her profile was fake. Bumble's editorial director Clare O'Connor reached out to the celebrity on Twitter to notify that her account was unblocked, and signed off with the message- "hope you find your honey." AHA! @sharonstone, we at @bumble found your account, unblocked you, and ensured this won't happen again. You can get back to Bumbling! Thanks for bearing with us and hope you find your honey.

Samsung is gearing up to unveil a new artificial intelligence that it says will be smart enough to become one's'best friend.' The AI, called Neon, will be unveiled in the coming week at the Consumer Electronics Show (CES) in Las Vegas and according to Samsung, will go above and beyond the capabilities of the tech giant's current voice assistant, 'Bixby.' 'Honored to have so much coverage even before we unveil. But contrary to some news, NEON is NOT about Bixby, or anything you have seen before. While details about what Neon will actually do are sparse, the company has suggested that it will be smart enough to act as a kind of AI companion, or'best friend.' Samsung has also been careful about the language it has used to describe Neon.

A data leak by smart home device manufacturer Wyze left the personal details of 2.4 million users exposed on the internet for more than three weeks. Among the compromised information was user email addresses, WiFi network names, smart device details and the health statistics of a limited number of users. Founded by former Amazon employees, the Seattle, Washington-based firm specialises in inexpensive smart cameras, light bulbs, plugs and security devices. Wyze has now secured the database and forced users to reset their account passwords, as well as their connections with other services like Amazon's Alexa or Google assistant. A data leak by smart home device manufacturer Wyze left the personal details of 2.4 million users exposed on the internet for more than three weeks.

Fox News Flash top entertainment and celebrity headlines for Dec. 30 are here. Check out what's clicking today in entertainment. It's all fun and games until you get blocked. Actress Sharon Stone revealed that she joined the dating app Bumble until her account was suddenly blocked, and she took to social media to voice her frustration. "I went on the @bumble dating sight and they closed my account. "Some users reported that it couldn't possibly be me!

Anyone that has ever spoken the words "Hey Siri" or "OK Google" into their phone knows how to use voice assistants. The revolution of digital and artificial intelligence is affecting more and more aspects of our lives and businesses. It is being used to create bots for automation or to simply make sense of the billions of datasets that are being generated daily. Generally, when it comes to artificial intelligence it is all about making processes easier or better. Especially while dealing with customer interactions the new possibilities of AI, most prominently chatbots are creating a more enjoyable customer experience.

Neurodiversity is the concept of neurological differences observed in human variations. Historically, these differences have been labeled as Autistic Spectrum, Dyspraxia, Dyslexia, ADHD, etc.. At times, we were quick to call neurodivergence a developmental disorder or a disease. But, we know much more now. Neurodiversity is a competitive advantage.

Recommender Systems (RS) have became a popular research topic and, since 2016, Deep Learning methods and techniques have been increasingly explored in this area. News RS are aimed to personalize users experiences and help them discover relevant articles from a large and dynamic search space. The main contribution of this research was named CHAMELEON, a Deep Learning meta-architecture designed to tackle the specific challenges of news recommendation. It consists of a modular reference architecture which can be instantiated using different neural building blocks. As information about users' past interactions is scarce in the news domain, the user context can be leveraged to deal with the user cold-start problem. Articles' content is also important to tackle the item cold-start problem. Additionally, the temporal decay of items (articles) relevance is very accelerated in the news domain. Furthermore, external breaking events may temporally attract global readership attention, a phenomenon generally known as concept drift in machine learning. All those characteristics are explicitly modeled on this research by a contextual hybrid session-based recommendation approach using Recurrent Neural Networks. The task addressed by this research is session-based news recommendation, i.e., next-click prediction using only information available in the current user session. A method is proposed for a realistic temporal offline evaluation of such task, replaying the stream of user clicks and fresh articles being continuously published in a news portal. Experiments performed with two large datasets have shown the effectiveness of the CHAMELEON for news recommendation on many quality factors such as accuracy, item coverage, novelty, and reduced item cold-start problem, when compared to other traditional and state-of-the-art session-based recommendation algorithms.